On Wired, a fascinating look at what can be understood looking at the metadata of 3 billion tweets. One such thing, as this gallery displays, the concentration of iPhones versus Android devices depending on the neighbourhood. I wonder what other data -- income, trendiness, education? -- could be correlated with this.
If its possible for a concept to have fifteen minutes of fame, ?metadata? had its own a few weeks ago, when it was revealed that Verizon was passing the stuff off en masse to the National Security Agency. In that case, we learned, the information being handed over wasnt the actual content of phone calls but rather all the stuff surrounding it the metadata of who was calling whom, from where, and for how long. Many were quick to point out that this seemingly innocuous information could actually reveal quite a bit about individual subscribers. These maps, however, show us how Big Metadata can be used for decidedly less nefarious ends. Like redrawing cities based on which neighborhoods use Android and which use iPhone.
The visualizations were created by engineers at MapBox, an enterprise mapping outfit, in collaboration with Eric Fischer, the data viz whiz whose maps of racial and ethnic make-up in American cities travelled widely across the web a few years back. In this case, the metadata doesnt come from phone calls but from tweets three billion of them, to be exact, or every geotagged message since roughly September, 2011, slurped up directly from the Twitter fire hose by the social media data specialists at Gnip. And while an individual tweet stripped of its actual data isnt all that interesting, in aggregate, they prove surprisingly illuminating.
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